Generally, in the context of natural language processing or understanding, before a specific action is performed in response to a natural language (NL) input, an information domain (from a plurality of pre-configured information domains) to which the NL input belongs is identified or determined (with a particular likelihood). By classifying an NL input to a particular domain, a natural language understanding (NLU) system may extract possible intent of the NL input, and identify or determine specific computer-executable actions related to that information domain, which, when executed, are responsive to the intended request in the NL input.
However, based on the complexity of the NL input and capabilities of (e.g., scope of the grammar configured for) the NLU system, the domain for the NL input may not be correctly determined. This may result in incorrect or unintended actions being executed in response to the NL input, resulting in an inefficient and unsatisfactory user experience. These and other drawbacks exist.